Metabolomics for tea authentication and fraud detection: Recent applications and future directions.

With 86.2% of tea production in Asia, teas consumed in other parts of the world are usually imported. The intricacies of the supply chain make tea vulnerable to fraudulent activities, highlighting the importance of ensuring authenticity and detecting fraud committed in teas. Conventionally, tea authentication is done by sensory evaluation. Moreover, the standardised chemical analysis techniques used for the evaluation of tea quality and authenticity are laborious. Thus, metabolomics, particularly the non-targeted metabolic fingerprinting approach, has been increasingly applied for high throughput authentication of tea. A brief overview of the metabolomics approach is provided. Then, this review delves into recent applications (i.e., from 2017 to 2023) of metabolomics to detect fraud committed in the form of mislabelling, substitution adulteration, and artificial enhancement. It concludes with future directions that could be undertaken. Targeted and non-targeted metabolomics were found to be largely successful in authenticating tea and detecting fraud. There is a growing interest in the use of non-targeted fingerprinting approach using rapid, non-destructive, and easy-to-use analytical platforms (e.g., vibrational spectroscopy, hyperspectral imaging). These techniques provide the possibility for high-throughput, large-scale, and point-of-site screening of teas. Nonetheless, more work on building a reliable database of chemical fingerprints/profiles for future authentication efforts and developing a tier-based approach for a confident confirmation of fraudulent activity perpetrated in tea is needed. • Tea is one of the food categories with high rates of fraud. • Metabolomics can complement conventional methods for tea authentication. • Metabolomics using rapid tools are useful for high-throughput screening of teas. • Metabolomics approaches to tackle various categories of tea fraud were detailed. [ABSTRACT FROM AUTHOR]